The main advantage of deep learning algorithms is that they are very fast at inference, one second per image compared to the 30 seconds a human needed on average, and they are more scalable. This allows us to apply the algorithm to the entire globe (Fig. REF a; see Supplement for details). A healthy skepticism is warranted when applying machine learning algorithms outside of their training regime [1]}, [2]}. A visual inspection of the global maps (see [3]} for more examples), however, suggests that the algorithm's predictions are reasonable and physically interpretable as discussed below. Naturally, over land the predictions have to be assessed with greater care because no land was present in the training dataset. Nevertheless, Fig. REF a suggests that the algorithm even appears to correctly identify shallow cumuli over the tropical landmasses as sugar.
